Stereo block matching methods are typically used for creating disparity maps by mapping or comparing pairs of rectified images. The rectified images are matched using a dense correspondence for every pixel in the left image into the right image.
Pyramid based methods are typically used for coarse to fine computations. However, the pyramid approach for stereo based matching typically results in poor recovery of thin objects. Thin objects get lost in coarse higher levels of the pyramid due to the low resolution. For example, a finger object in an image in a coarsest level may include a thin object represented by only two or three pixels. As coarse levels have less information about high frequencies, the finger object may not be visible and may blend into the background. It is with respect to these and other considerations that the present improvements have been needed.